Upon utilizing a search application of the Internet or in an information device such as a car navigation system, portable phone, or the like, information associated with a place such as a station name, landmark, address, or the like is often input. Speech recognition may be used to input such information. Now assuming an application which recognizes station names input by speech upon inputting departure and destination stations in association with a route guide of train. In this case, since all station names assumed by the application are used as objects to be inputs, around 10 thousand station names are lexical items which are to undergo speech recognition. The speech recognition performance of isolated words when several thousand or more lexical items are to be recognized in this way is not sufficient in the current speech recognition technique.
When each individual user uses such application, even when words to be recognized are nationwide ones, the area of the station names to be frequently input by the user are often relatively limited to those around his or her home or place of work. For example, if an utterance of the user who frequently inputs station names around Yokohama and Tokyo is recognized to have the same likelihood value as “(Tanimachi)” or “(Tanmachi)”, it is normally considered that “(Tanmachi)” in Yokohama is more probable than “(Tanimachi)” in Osaka. That is, the speech recognition performance can be improved by utilizing information obtained from user's previous input history in current speech recognition.
By contrast, Japanese Patent Laid-Open No. 11-231889 discloses a method of correcting similarity data output from a speech recognition device in accordance with the distance from the current position where speech recognition is used, the name recognition of a landmark, or the like in recognition of a place name, landmark, and the like.
Also, Japanese Patent No. 2907728 discloses a method of calculating the frequencies of occurrence of an area where an automobile traveled previously, and an area of a destination, and calculating the recognition result in consideration of the frequencies of occurrence.
Japanese Patent Laid-Open No. 11-231889 above also discloses a method of directly utilizing the recognition history, but it does not mention about correction of similarity data around the recognition history. Hence, similarity data of place names around those which were input previously and place name of areas which were not input previously at all cannot be corrected.
Also, since the method disclosed in Japanese Patent No. 2907728 divides destinations as areas which do not overlap each other, an area with zero frequency of occurrence around the area where the automobile travels frequently and a plurality of areas where the automobile did not travel at all are equally handled.